If you are looking for an answer to the question What is Artificial Intelligence? and you only have a minute, then here's the definition the Association for the Advancement of Artificial Intelligence offers on its home page: "the scientific understanding of the mechanisms underlying thought and intelligent behavior and their embodiment in machines."
However, if you are fortunate enough to have more than a minute, then please get ready to embark upon an exciting journey exploring AI (but beware, it could last a lifetime) …
This article is a summary of a three-hour discussion at Stanford University in September 2019 among the authors. It has been written with combined experiences at and with organizations such as Zilog, Altera, Xilinx, Achronix, Intel, IBM, Stanford, MIT, Berkeley, University of Wisconsin, the Technion, Fairchild, Bell Labs, Bigstream, Google, DIGITAL (DEC), SUN, Nokia, SRI, Hitachi, Silicom, Maxeler Technologies, VMware, Xerox PARC, Cisco, and many others. These organizations are not responsible for the content, but may have inspired the authors in some ways, to arrive at the colorful ride through FPGA space described here. Field-programmable gate arrays (FPGAs) have been hitting a nerve in the ASIC community since their inception. In the mid-1980s, Ross Freeman and his colleagues bought the technology from Zilog and started Xilinx, targeting the ASIC emulation and education markets.
Frances E. Allen, an American computer scientist, ACM Fellow, and the first female recipient of the ACM A.M. Turing Award (2006), passed away on Aug. 4, 2020--her 88th birthday--from complications of Alzheimer's disease. Allen was raised on a dairy farm in Peru, NY, without running water or electricity. She received a BS degree in mathematics from the New York State College for Teachers (now the State University of New York at Albany). Inspired by a beloved math teacher, and by the example of her mother, who had also been a grade-school teacher, Allen started teaching high school math. She needed a master's degree to be certified, so she enrolled in a mathematics master's program at the University of Michigan.
RingCentral, Inc., a leading provider of global enterprise cloud communications, collaboration, and contact center solutions, announced that its unified communications platform including team messaging, video meetings, and cloud phone system will now be available in Germany with a new data center in Frankfurt, and a new office in Hamburg, Germany. As RingCentral continues its global expansion efforts, Germany remains a key strategic location for the company. The new data center will also give users access to local phone numbers and emergency services in compliance with local laws and regulations. RingCentral will offer customers local data storage, the ability to register endpoints in-country and keep voice and video call media local. The new datacenter will also give users access to local phone numbers and emergency services in compliance with local laws and regulations.
Earlier in the year, Microsoft detailed the ways Bing has benefited from AI at Scale, an initiative to apply large-scale AI and supercomputing to language processing across Microsoft's apps, services, and managed products. AI at Scale chiefly bolstered the search engine's ability to directly answer questions and generate image captions, but in a blog post today, Microsoft says it's led to Bing improvements in things like autocomplete suggestions. Bing and its competitors have a lot to gain from AI and machine learning, particularly in the natural language domain. Search engines need to comprehend queries no matter how confusingly they're worded, but they've historically struggled with this, leaning on Boolean operators (simple words like "and," "or," and "not") as band-aids to combine or exclude search terms. But with the advent of AI like Google's BERT and Microsoft's Turing family, search engines have the potential to become more conversationally and contextually aware than perhaps ever before.
Companies in all business sectors are competing to recruit top-notch AI teams, but are these investments productive? With millions worldwide working in AI now, and over 90% of mid-size and larger companies having specialized AI or Data Science teams, researchers and engineers in this field are literally drowning in the pace of innovation. Per day, an AI expert needs to scan several hundred new research publications to stay up to date. Leading researchers, like Yoshua Bengio and Yann LeCun, openly admit they find it impossible to keep up. Amsterdam based startup Zeta Alpha is now launching AI Research Navigator, a new deep learning-based search platform, to help AI experts with this.
Microsoft has been working to deliver a knowledge-management service for several years. Last year, at its Ignite IT Pro conference, it officially announced plans for its latest iteration of such a service under the codename "Project Cortex." At this year's Ignite, Microsoft is announcing the revamp of Cortex, as well as its plans for the rollout of the first few Cortex components. Up until this week, it seemed as if Project Cortex was going to be a single, centralized service that could be accessed inside existing Microsoft applications like Outlook, SharePoint, and more. Microsoft officials had been calling Cortex the first new major Microsoft 365 service since Microsoft Teams was launched in 2017.
Let's now look at some of the useful sites for finding open and publicly available datasets, quickly and without much hassle. Google Dataset Search is a search engine dedicated to finding datasets. It is a search engine over metadata from data providers. This implies that it indexes over the descriptions of a dataset instead of its content. So if a dataset is available publicly, there is a good chance, that it will pop up in the Google dataset search.
People who consume online media are constantly changing. These days, they look for instantaneous insights and results; making the role of machine learning even more important in SEO. Marketers only need to look at recent developments with Google's RankBrain to get a sense of how important it is to search marketing. Current machine-based technology can boost business productivity by up to 40%, according to Accenture. If you still aren't sure how machine learning is changing SEO, it's time to pay attention.